R

Elijah Mercer

Consulting Drop-In Hours: Mon 3pm-5pm

Consulting Areas: Python, R, Data Sources, Mixed Methods, Qualitative methods, Surveys, Sampling & Interviews, Excel, Qualtrics

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Elena Stacy

Consulting Drop-In Hours: Mon 9am-11am

Consulting Areas: R, Stata, LaTeX, Data Manipulation and Cleaning, Data Sources, Data Visualization, Geospatial Data, Maps & Spatial Analysis, R Programming, Surveys, Sampling & Interviews, Text Analysis, Web Scraping, Regression Analysis, Means Tests, Excel, Git or Github, QGIS, RStudio, Stata

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Reine Ngnonsse

IUSE Undergraduate Advisory Board
Genetics and Plant Biology

Reine Ngnonsse, an enthusiast for math and technology, delved into tutoring math at a community college through the EOPs program. At UC Berkeley, while pursuing Genetics and Plant Biology, She explored R programming in a CRISPR project. As an intern at Health Career Connection, Reine expanded coding skills in Python, R, and Tableau, igniting a passion for programming. With exposure to Python and Javascript, she can't wait to merge mathematical prowess with coding finesse for innovative solutions.

Addison Pickrell

IUSE Undergraduate Advisory Board
Mathematics
Sociology

Addison is an aspiring mathematician and social scientist (Class of '27). He loves collecting books he'll never read, is an open-source and open-access advocate, and an aspiring community organizer and systems disrupter. Ask me about community-based participatory action research (CBPAR), critical pedagogy, applied mathematics, and social science.

Larissa Benjamin

Doctor of Public Health Student
Public Health

Larissa Benjamin is a second year Doctor of Public Health (DrPH) student at UC Berkeley. Her research uses a mixed-methods approach to exploring the structural determinants of cardiovascular disease inequities in the rural Southeastern United States, also called the “Stroke Belt.” She is particularly curious about how regional history, geography, and structural racism shape inequitable rural neighborhood risk environments. Larissa earned a BS in Evolutionary Anthropology and English from University of Michigan, and an MPH at UC Berkeley in Health and Social Behavior with a...

Paul Salamanca

Instructor
Sociology

I am a PhD student in sociology. I study imperialism, race, and gender, with a historical focus on the colonial Philippines. In my free time, I like to cook and bake.

Mapping Census Data with tidycensus

November 6, 2023
Alex Ramiller
by Alex Ramiller. The U.S. Census Bureau provides a rich source of publicly available data for a wide variety of research applications. However, the traditional process of downloading these data from the census website is slow, cumbersome, and inefficient. The R package “tidycensus” provides researchers with a tool to overcome these challenges, enabling a streamlined process to quickly downloading numerous datasets directly from the census API (Application Programming Interface). This blog post provides a basic workflow for the use of the tidycensus package, from installing the package and identifying variables to efficiently downloading and mapping census data.

Hate Speech

The hate speech measurement project began in early 2017 at UC Berkeley’s D-Lab. Our research project applies data science techniques such as machine learning to track changes in hate speech over time and across social media platforms. After three years, we have now published our groundbreaking method that measures hate speech with precision while mitigating the influence of human bias. Read the manuscript here.

Introduction to Item Response Theory

October 24, 2023
Mingfeng Xue
by Mingfeng Xue. Measurements (e.g., tests, surveys, questionnaires) are inevitably involved with various sources of errors. Among many psychometric theories, item response theory stands out for its capability of detailed analyses at the item level and its potential to reduce some of the measurement errors. This post first discussed the limitations of conventional summation and average, which give rise to the IRT models, and then introduced a basic form of the Rasch model, including expressions of the model, the assumptions underlying it, some of its advantages, and software packages. Some codes are also provided.

Anusha Bishop

Consulting Drop-In Hours: Mon 10am-12pm

Consulting Areas: Python, R, Cloud & HPC Computing, Data Sources, Data Visualization, Geospatial Data, Maps & Analysis, Machine Learning, Research Design, Causal inference, Cluster analysis, Experimental design, Hierarchical Models, High dimensional statistics, Means Tests, Nonparametric methods, Regression Analysis, Software Output Interpretation, Spatial statistics, Bash or Command Line, Excel, Git or Github, RStudio

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